Factors Associated With Surveillance Testing in Individuals With COVID-19 Symptoms During the Last Leg of the Pandemic: Multivariable Regression Analysis

Overview

Journal JMIR Public Health Surveill

Publisher JMIR Publications

Date 2024 Jul 20

PMID 39030676

Authors

Timothy Dotson

Brad Price

Brian Witrick

Sherri Davis

Emily Kemper

Stacey Whanger

Sally Hodder

Brian Hendricks

Affiliations

Soon will be listed here.

Abstract

Background: Rural underserved areas facing health disparities have unequal access to health resources. By the third and fourth waves of SARS-CoV-2 infections in the United States, COVID-19 testing had reduced, with more reliance on home testing, and those seeking testing were mostly symptomatic.

Objective: This study identifies factors associated with COVID-19 testing among individuals who were symptomatic versus asymptomatic seen at a Rapid Acceleration of Diagnostics for Underserved Populations phase 2 (RADx-UP2) testing site in West Virginia.

Methods: Demographic, clinical, and behavioral factors were collected via survey from tested individuals. Logistic regression was used to identify factors associated with the presence of individuals who were symptomatic seen at testing sites. Global tests for spatial autocorrelation were conducted to examine clustering in the proportion of symptomatic to total individuals tested by zip code. Bivariate maps were created to display geographic distributions between higher proportions of tested individuals who were symptomatic and social determinants of health.

Results: Among predictors, the presence of a physical (adjusted odds ratio [aOR] 1.85, 95% CI 1.3-2.65) or mental (aOR 1.53, 95% CI 0.96-2.48) comorbid condition, challenges related to a place to stay/live (aOR 307.13, 95% CI 1.46-10,6372), no community socioeconomic distress (aOR 0.99, 95% CI 0.98-1.00), no challenges in getting needed medicine (aOR 0.01, 95% CI 0.00-0.82) or transportation (aOR 0.23, 95% CI 0.05-0.64), an interaction between community socioeconomic distress and not getting needed medicine (aOR 1.06, 95% CI 1.00-1.13), and having no community socioeconomic distress while not facing challenges related to a place to stay/live (aOR 0.93, 95% CI 0.87-0.99) were statistically associated with an individual being symptomatic at the first test visit.

Conclusions: This study addresses critical limitations to the current COVID-19 testing literature, which almost exclusively uses population-level disease screening data to inform public health responses.

Citing Articles

COVID-19 Testing Behavior as a Predictor of COVID-19 Vaccination in Southeastern Louisiana: A Longitudinal Cohort Study.

Al-Dahir S, Barri S, Heyer K, Taylor A, Khalil A, Belkhouche M Vaccines (Basel). 2025; 12(12).

PMID: 39772000 PMC: 11679823. DOI: 10.3390/vaccines12121338.

References

Tromberg B, Schwetz T, Perez-Stable E, Hodes R, Woychik R, Bright R . Rapid Scaling Up of Covid-19 Diagnostic Testing in the United States - The NIH RADx Initiative. N Engl J Med. 2020; 383(11):1071-1077. PMC: 7493127. DOI: 10.1056/NEJMsr2022263. View

Maharaj A, Parker J, Hopkins J, Gournis E, Bogoch I, Rader B . The effect of seasonal respiratory virus transmission on syndromic surveillance for COVID-19 in Ontario, Canada. Lancet Infect Dis. 2021; 21(5):593-594. PMC: 7993926. DOI: 10.1016/S1473-3099(21)00151-1. View

Clark A, Jit M, Warren-Gash C, Guthrie B, Wang H, Mercer S . Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study. Lancet Glob Health. 2020; 8(8):e1003-e1017. PMC: 7295519. DOI: 10.1016/S2214-109X(20)30264-3. View

Yang W, Zhang D, Peng L, Zhuge C, Hong L . Rational evaluation of various epidemic models based on the COVID-19 data of China. Epidemics. 2021; 37:100501. PMC: 8464399. DOI: 10.1016/j.epidem.2021.100501. View

Kaufman B, Whitaker R, Pink G, Holmes G . Half of Rural Residents at High Risk of Serious Illness Due to COVID-19, Creating Stress on Rural Hospitals. J Rural Health. 2020; 36(4):584-590. PMC: 7361543. DOI: 10.1111/jrh.12481. View

Graham M, May A, Varsavsky T, Sudre C, Murray B, Klaser K . Knowledge barriers in a national symptomatic-COVID-19 testing programme. PLOS Glob Public Health. 2023; 2(1):e0000028. PMC: 10022193. DOI: 10.1371/journal.pgph.0000028. View

Shea D, Stuart B, Vasey J, Nag S . Medicare physician referral patterns. Health Serv Res. 1999; 34(1 Pt 2):331-48. PMC: 1089005. View

Althubaiti A . Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016; 9:211-7. PMC: 4862344. DOI: 10.2147/JMDH.S104807. View

Corbie G, M DAgostino E, Knox S, Richmond A, Woods C, Dave G . RADx-UP Coordination and Data Collection: An Infrastructure for COVID-19 Testing Disparities Research. Am J Public Health. 2022; 112(S9):S858-S863. PMC: 9707715. DOI: 10.2105/AJPH.2022.306953. View

10.

Ahillan T, Emmerson M, Swift B, Golamgouse H, Song K, Roxas A . COVID-19 in the homeless population: a scoping review and meta-analysis examining differences in prevalence, presentation, vaccine hesitancy and government response in the first year of the pandemic. BMC Infect Dis. 2023; 23(1):155. PMC: 10012317. DOI: 10.1186/s12879-023-08037-x. View

11.

Allen W, Altae-Tran H, Briggs J, Jin X, McGee G, Shi A . Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing. Nat Hum Behav. 2020; 4(9):972-982. PMC: 7501153. DOI: 10.1038/s41562-020-00944-2. View

12.

Huttlinger K, Schaller-Ayers J, Lawson T . Health care in Appalachia: a population-based approach. Public Health Nurs. 2004; 21(2):103-10. DOI: 10.1111/j.0737-1209.2004.021203.x. View

13.

Thorne L, Bouhaddou M, Reuschl A, Zuliani-Alvarez L, Polacco B, Pelin A . Evolution of enhanced innate immune evasion by SARS-CoV-2. Nature. 2021; 602(7897):487-495. PMC: 8850198. DOI: 10.1038/s41586-021-04352-y. View

14.

Lauring A, Tenforde M, Chappell J, Gaglani M, Ginde A, McNeal T . Clinical severity of, and effectiveness of mRNA vaccines against, covid-19 from omicron, delta, and alpha SARS-CoV-2 variants in the United States: prospective observational study. BMJ. 2022; 376:e069761. PMC: 8905308. DOI: 10.1136/bmj-2021-069761. View

15.

Aleta A, Martin-Corral D, Pastore Y Piontti A, Ajelli M, Litvinova M, Chinazzi M . Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19. Nat Hum Behav. 2020; 4(9):964-971. PMC: 7641501. DOI: 10.1038/s41562-020-0931-9. View

16.

Price B, Khodaverdi M, Halasz A, Hendricks B, Kimble W, Smith G . Predicting increases in COVID-19 incidence to identify locations for targeted testing in West Virginia: A machine learning enhanced approach. PLoS One. 2021; 16(11):e0259538. PMC: 8565789. DOI: 10.1371/journal.pone.0259538. View

17.

Hawkins R, Charles E, Mehaffey J . Socio-economic status and COVID-19-related cases and fatalities. Public Health. 2020; 189:129-134. PMC: 7568122. DOI: 10.1016/j.puhe.2020.09.016. View

18.

Hendricks B, Price B, Dotson T, Kimble W, Davis S, Khodaverdi M . If you build it, will they come? Is test site availability a root cause of geographic disparities in COVID-19 testing?. Public Health. 2023; 216:21-26. PMC: 9485419. DOI: 10.1016/j.puhe.2022.09.009. View

19.

Kirby J, Yabroff K . Rural-Urban Differences in Access to Primary Care: Beyond the Usual Source of Care Provider. Am J Prev Med. 2019; 58(1):89-96. DOI: 10.1016/j.amepre.2019.08.026. View

20.

Hendricks B, Paul R, Smith C, Wen S, Kimble W, Amjad A . Coronavirus testing disparities associated with community level deprivation, racial inequalities, and food insecurity in West Virginia. Ann Epidemiol. 2021; 59:44-49. PMC: 9558346. DOI: 10.1016/j.annepidem.2021.03.009. View